Gene Expression Biclustering

# load data in 'global' chunk so it can be shared by all users of the dashboard
library(biclust)
data(BicatYeast)
set.seed(1)
res <- biclust(BicatYeast, method=BCPlaid(), verbose=FALSE)

Inputs {.sidebar}

 selectInput("clusterNum", label = h3("Cluster number"), 
    choices = list("1" = 1, "2" = 2, "3" = 3, "4" = 4, "5" = 5), 
    selected = 1)

Microarray data matrix for 80 experiments with Saccharomyces Cerevisiae organism extracted from R's biclust package.

Sebastian Kaiser, Rodrigo Santamaria, Tatsiana Khamiakova, Martin Sill, Roberto Theron, Luis Quintales, Friedrich Leisch and Ewoud De Troyer. (2015). biclust: BiCluster Algorithms. R package version 1.2.0. http://CRAN.R-project.org/package=biclust

Row

Heatmap

num <- reactive(as.integer(input$clusterNum))

col = colorRampPalette(c("red", "white", "darkblue"), space="Lab")(10)
renderPlot({
    p = par(mai=c(0,0,0,0))
    heatmapBC(BicatYeast, res, number=num(), xlab="", ylab="",
      order=TRUE, useRaster=TRUE, col=col)
    par(p)
})

Row {.tabset}

Parallel Coordinates

renderPlot(
  parallelCoordinates(BicatYeast, res, number=num())
)

Data for Selected Cluster

# only display table for values in cluster 4
renderTable(
  BicatYeast[which(res@RowxNumber[, num()]), which(res@NumberxCol[num(), ])]
)


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flexdashboard documentation built on July 8, 2020, 7:32 p.m.